AR Sensor Placement for Accurate Remote Goniometer Positioning
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Solution Overview
Problem
Telemedicine systems face challenges in remotely monitoring patient progress and adapting treatment plans due to the inability of healthcare providers to conduct physical examinations, leading to inefficiencies and inaccuracies in treatment plan selection and implementation.
Innovation Solution
A system utilizing artificial intelligence and machine learning to assign patients to cohorts based on their characteristics, dynamically control treatment apparatuses, and generate personalized treatment plans in real-time, incorporating sensor data and user interfaces for enhanced telemedical sessions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If telemedicine systems are used for remote patient monitoring, then healthcare providers can communicate with patients remotely, but the providers cannot conduct physical examinations leading to inaccuracies in treatment plan selection
Solution Approach 1:
The patent introduces an intermediary system comprising sensors, processors, and communication modules that bridge the gap between remote healthcare providers and patients. The system captures physical examination data through multiple sensors (visual, auditory, tactile) and transmits it to providers, enabling accurate remote assessment without direct physical contact.
Solution Approach 2:
The patent replaces the mechanical physical examination process with an electronic sensing system. Instead of providers manually examining patients, the system uses sensors to detect physiological parameters, movement, and environmental conditions, converting mechanical inspection into electronic data transmission for remote analysis.
2Adaptability or versatility
If multiple sensors are integrated into the treatment apparatus, then real-time patient monitoring and treatment adaptation is improved, but the device complexity increases
Solution Approach 1:
The patent divides the sensing system into separate functional modules, each responsible for specific measurements (movement sensors, physiological sensors, environmental sensors). This segmentation allows independent optimization of each sensor type while maintaining overall system coherence through centralized processing.
Solution Approach 2:
The patent creates a universal data processing framework that handles multiple sensor types through a common architecture. The processor receives data from diverse sensors (accelerometers, heart rate monitors, temperature sensors) and processes them through unified algorithms, reducing the need for separate processing systems for each sensor type.
3Measurement precision
If comprehensive sensor data is collected and processed, then treatment plan accuracy is improved, but computational resources and processing time increase
Solution Approach 1:
The patent performs preliminary data processing and feature extraction at the sensor level before transmission to the central processing system. Each sensor module pre-processes its data to identify key parameters and filter noise, reducing the volume of data that requires intensive computational analysis and lowering overall energy consumption.
Solution Approach 2:
The patent extracts and transmits only the most critical diagnostic information from the comprehensive sensor data rather than all raw data. The system identifies and transmits key features (e.g., movement range, physiological anomalies) while filtering out redundant information, significantly reducing computational load while maintaining treatment accuracy.
Data Source
AI summary
Systems and methods for positioning one or more sensors on a user. The system has user sensors, apparatus sensors, and treatment sensors. A processing device, executing computer readable instructions stored in a memory, cause the processing device to: generate an enhanced environment representative of an environment; receive apparatus data representative of a location of the apparatus in the environment; generate an apparatus avatar in the enhanced environment; receive user data representative of a location of the user in the environment; generate a user avatar in the enhanced environment; receive treatment data representative of one or more locations of the treatment sensors in the environment; generate, treatment sensor avatars in the enhanced environment; calculate a treatment location for each treatment sensor, wherein the treatment location is associated with an anatomical structure of a user; and generate instruction data representing an instruction for positioning the treatment sensors at the treatment location.


